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Found 11 papers, 3 papers with code
PanoContext-Former: Panoramic Total Scene Understanding with a Transformer
Panoramic image enables deeper understanding and more holistic perception of $360^\circ$ surrounding environment, which can naturally encode enriched scene context information compared to standard perspective image.
Task-aware Adaptive Learning for Cross-domain Few-shot Learning
In this paper, we first observe the dependence of task-specific parameter configuration on the target task.
PanoViT: Vision Transformer for Room Layout Estimation from a Single Panoramic Image
In this paper, we propose PanoViT, a panorama vision transformer to estimate the room layout from a single panoramic image.
Caption Feature Space Regularization for Audio Captioning
To eliminate this negative effect, in this paper, we propose a two-stage framework for audio captioning: (i) in the first stage, via the contrastive learning, we construct a proxy feature space to reduce the distances between captions correlated to the same audio, and (ii) in the second stage, the proxy feature space is utilized as additional supervision to encourage the model to be optimized in the direction that benefits all the correlated captions.
Modeling Clothing as a Separate Layer for an Animatable Human Avatar
To address these difficulties, we propose a method to build an animatable clothed body avatar with an explicit representation of the clothing on the upper body from multi-view captured videos.
TLRM: Task-level Relation Module for GNN-based Few-Shot Learning
We consider this method of measuring relation of samples only models the sample-to-sample relation, while neglects the specificity of different tasks.
Inverse Structural Design of Graphene/Boron Nitride Hybrids by Regressional GAN
A significant novelty of the proposed RGAN is that it combines the supervised and regressional convolutional neural network (CNN) with the traditional unsupervised GAN, thus overcoming the common technical barrier in the traditional GANs, which cannot generate data associated with given continuous quantitative labels.
Computational Physics Materials Science Applied Physics
MSFD:Multi-Scale Receptive Field Face Detector
We simultaneously propose an anchor assignment strategy which can cover faces with a wide range of scales to improve the recall rate of small faces and rotated faces.
Multi-hierarchical Independent Correlation Filters for Visual Tracking
For visual tracking, most of the traditional correlation filters (CF) based methods suffer from the bottleneck of feature redundancy and lack of motion information.
Deep Learning Bandgaps of Topologically Doped Graphene
Moreover, given ubiquitous existence of topologies in materials, this work will stimulate widespread interests in applying deep learning algorithms to topological design of materials crossing atomic, nano-, meso-, and macro- scales.
Materials Science Computational Physics
BodyFusion: Real-Time Capture of Human Motion and Surface Geometry Using a Single Depth Camera
To reduce the ambiguities of the non-rigid deformation parameterization on the surface graph nodes, we take advantage of the internal articulated motion prior for human performance and contribute a skeleton-embedded surface fusion (SSF) method.
